检索结果-内蒙古大学图书馆

26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

引用

BMC NEUROscience 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

来源：评论

学校读者我要写书评

暂无评论

Blind identification strategies for room occupancy estimation

Blind identification strategies for room occupancy estimatio...

引用

European control Conference

作者： A. Ebadat G. Bottegal D. Varagnolo B. Wahlberg H. Hjalmarsson K. H. Johansson ACCESS the Department of Automatic Control School of Electrical engineering KTH Royal Institute of Technology Division of Signals and Systems Department of Computer Science Electrical and Space Engineering Lulea University of Innovation and Technology

ISBN: (纸本)9781467371605

We propose and test on real data a two-tier estimation strategy for inferring occupancy levels from measurements of CO_2 concentration and temperature levels. The first tier is a blind identification step, based either on a frequentist Maximum Likelihood method, implemented using non-linear optimization, or on a Bayesian marginal likelihood method, implemented using a dedicated Expectation-Maximization algorithm. The second tier resolves the ambiguity of the unknown multiplicative factor, and returns the final estimate of the occupancy levels. The overall procedure addresses some practical issues of existing occupancy estimation strategies. More specifically, first it does not require the installation of special hardware, since it uses measurements that are typically available in many buildings. Second, it does not require apriori knowledge on the physical parameters of the building, since it performs system identification steps. Third, it does not require pilot data containing measured real occupancy patterns (i.e., physically counting people for some periods, a typically expensive and time consuming step), since the identification steps are blind.

关键词： System identification Management of HVAC systems Maximum Likelihood Expectation-Maximization

来源：评论

学校读者我要写书评

暂无评论

Multi-room occupancy estimation through adaptive gray-box models

Multi-room occupancy estimation through adaptive gray-box mo...

引用

IEEE Annual Conference on decision and control

作者： A. Ebadat G. Bottegal M. Molinari D. Varagnolo B. Wahlberg H. Hjalmarsson K. H. Johansson ACCESS and the Department of Automatic Control School of Electrical engineering KTH Royal Institute of Technology Sweden Division of Signals and Systems Department of Computer Science Electrical and Space Engineering Lulea University of Innovation and Technology Lulea Sweden

ISBN: (纸本)9781479978878

We consider the problem of estimating the occupancy level in buildings using indirect information such as CO_2 concentrations and ventilation levels. We assume that one of the rooms is temporarily equipped with a device measuring the occupancy. Using the collected data, we identify a gray-box model whose parameters carry information about the structural characteristics of the room. Exploiting the knowledge of the same type of structural characteristics of the other rooms in the building, we adjust the gray-box model to capture the CO_2 dynamics of the other rooms. Then the occupancy estimators are designed using a regularized deconvolution approach which aims at estimating the occupancy pattern that best explains the observed CO_2 dynamics. We evaluate the proposed scheme through extensive simulation using a commercial software tool, IDA-ICE, for dynamic building simulation.

关键词： Vehicle Occupancy Rooms Structural properties Buildings building simulation BOX MODELS Carbon Dioxide

来源：评论

学校读者我要写书评

暂无评论

control Schemes for Passive Teleoperation systems over Wide Area Communication Networks with Time Varying Delay

引用

International Journal of Automation and computing 2014年第1期11卷 100-108页

作者： Shafiqul Islam Xiaoping P.Liu Abdulmotaleb El Saddik Lakmal Seneviratne Jorge Dias School of Information Technology and Engineering University of Ottawa School of Engineering and Applied Sciences Harvard University Robotics and Mechanical Engineering Khalifa University of Science & Technology Department of Systems and Computer Engineering Carleton University Electrical Engineering New York University Division of Engineering Kings College London Robotics and Electrical and Computer Engineering Khalifa University of Science & Technology Institute of Systems and Robotics University of Coimbra

In this paper,the problem of time varying telecommunication delays in passive teleoperation systems is *** design comprises delayed position,velocity and position-velocity signals with the local position and velocity signals of the master and slave *** adaptive control terms are employed locally to cope with uncertain parameters associated with the gravity loading vector of the master and slave ***-Krasovskii function is employed for three methods to establish asymptotic tracking property of the closed loop teleoperation *** stability analysis is derived for both symmetrical and unsymmetrical time varying delays in the forward and backward communication channel that connects the local and remote ***,evaluation results are presented to illustrate the efectiveness of the proposed design for real-time applications.

关键词： Teleoperation telerobotics Lyapunov-Krasovskii functional time varying delay passive systems

来源：评论

学校读者我要写书评

暂无评论

State Estimation of Finite-State Hidden Markov Models Subject to Stochastically Event-triggered Measurements

State Estimation of Finite-State Hidden Markov Models Subjec...

引用

IEEE Annual Conference on decision and control

作者： Wentao Chen Junzheng Wang Ling Shi Dawei Shi State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing 100081 P.R. China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

ISBN: (纸本)9781479978878

We consider the event-triggered state estimation of a finite-state hidden Markov model with a general stochastic event-triggering condition. Utilizing the change of probability measure approach and the event-triggered measurement information available to the estimator, analytical expressions for the conditional probability distributions of the states are obtained, based on which the minimum mean square error event-based state estimates are further calculated. We show that the results also cover the case of packet dropout, under a special parameterization of the event-triggering conditions. With the results on state estimation, a closed-form expression of the average sensor-to-estimator communication rate is also presented. The effectiveness of the proposed results is illustrated by a numerical example and comparative simulations.

关键词： State estimation Hidden Markov models Event trigger Probability distribution Mean square error numerical example

来源：评论

学校读者我要写书评

暂无评论

Space QUEST mission proposal: Experimentally testing decoherence due to gravity

arXiv

引用

arXiv 2017年

作者： Joshi, Siddarth Koduru Pienaar, Jacques Ralph, Timothy C. Cacciapuoti, Luigi McCutcheon, Will Rarity, John Giggenbach, Dirk Lim, Jin Gyu Makarov, Vadim Fuentes, Ivette Scheidl, Thomas Beckert, Erik Bourennane, Mohamed Bruschi, David Edward Cabello, Adan Capmany, Jose Carrasco-Casado, Alberto Diamanti, Eleni Dusek, Miloslav Elser, Dominique Gulinatti, Angelo Hadfield, Robert H. Jennewein, Thomas Kaltenbaek, Rainer Krainak, Michael A. Lo, Hoi-Kwong Marquardt, Christoph Milburn, Gerard Peev, Momtchil Poppe, Andreas Pruneri, Valerio Renner, Renato Salomon, Christophe Skaar, Johannes Solomos, Nikolaos Stipčević, Mario Torres, Juan P. Toyoshima, Morio Villoresi, Paolo Walmsley, Ian Weihs, Gregor Weinfurter, Harald Zeilinger, Anton Zukowski, Marek Ursin, Rupert Institute for Quantum Optics and Quantum Information Austrian Academy of Sciences Boltzmanngasse 3 ViennaA-1090 Austria Centre for Quantum Computation & Communication Technology Department of Physics University of Queensland St LuciaQLD4072 Australia European Space Agency Keplerlaan 1 - P.O. Box 299 AG Noordwijk ZH2200 Netherlands Department of Electrical and Electronic Engineering University of Bristol Merchant Venturers Building Woodland Road BristolBS8 1UB United Kingdom German Aerospace Center Institute of Communications and Navigation Muenchner Strasse 20 Wessling82234 Germany Institute for Quantum Computing Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Institute for Quantum Computing Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada Precision Engineering Department Fraunhofer IOF Albert-Einstein-Straße 7 Jena07745 Germany Physics department Stockholm University Albanova universitetscentrum Universitetsvägen 10 Stockholm114 18 Sweden York Centre for Quantum Technologies Department of Physics University of York HeslingtonYO10 5DD United Kingdom University of Seville SevillaE-41012 Spain iTEAM Research Institute Universitat Politcnica de Valencia Valencia46022 Spain 4-2-1 Nukui-Kitamachi Koganei Tokyo184-8795 Japan CNRS Universite Pierre et Marie Curie Paris75005 France Department of Optics Faculty of Science Palacky University 17. Iistopadu 12 Olomouc772 00 Czech Republic Max Planck Institute for the Science of Light Bldg. 24 Günther-Scharowsky Str. 1 ErlangenD-91058 Germany Piazza Leonardo da Vinci 32 Milano20133 Italy School of Engineering University of Glasgow GlasgowG12 8LT United Kingdom Vienna Center of Quantum Science and Technology Faculty of Physics University of Vienna Boltzmanngasse 5 ViennaA-1090 Austria NASA Goddard Space Flight Center GreenbeltMD20771 United States Center for Quantum Information and Quantum Con

Models of quantum systems on curved space-times lack sufficient experimental verification. Some speculative theories suggest that quantum properties, such as entanglement, may exhibit entirely different behavior to purely classical systems. By measuring this effect or lack thereof, we can test the hypotheses behind several such models. For instance, as predicted by Ralph and coworkers [T C Ralph, G J Milburn, and T Downes, Phys. Rev. A, 79(2):22121, 2009;T C Ralph and J Pienaar, New Journal of Physics, 16(8):85008, 2014], a bipartite entangled system could decohere if each particle traversed through a different gravitational field gradient. We propose to study this effect in a ground to space uplink scenario. We extend the above theoretical predictions of Ralph and coworkers and discuss the scientific consequences of detecting/failing to detect the predicted gravitational decoherence. We present a detailed mission design of the European Space Agency's (ESA) Space QUEST (Space - Quantum Entanglement Space Test) mission, and study the feasibility of the mission scheme. Copyright © 2017, The Authors. All rights reserved.

关键词： Quantum entanglement

来源：评论

学校读者我要写书评

暂无评论

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1

引用

BMC Neurosci 2017年第SUPPL 1期18卷 58-58页

作者： Sue Denham Panayiota Poirazi Erik De Schutter Karl Friston Ho Ka Chan Thomas Nowotny Dongqi Han Sungho Hong Sophie Rosay Tanja Wernle Alessandro Treves Sarah Goethals Romain Brette Tomas Van Pottelbergh Rodolphe Sepulchre Alex D. Bird Hermann Cuntz Pedro J. Gonçalves Jan-Matthis Lueckmann Giacomo Bassetto Marcel Nonnenmacher Jakob H. Macke Audrey J. Sederberg Jason N. MacLean Stephanie E. Palmer Ulisse Ferrari Christophe Gardella Olivier Marre Thierry Mora Emina Ibrahimovic Martin Müller Jean-Pascal Pfister Tushar Chauhan Timothée Masquelier Alexandre Montlibert Benoit R. Cottereau Moritz Helias Jannis Schuecker David Dahmen Sven Goedeke Alexandre Hyafil Ainhoa Hermoso-Mendizabal Pavel E. Rueda-Orozco Santiago Jaramillo David Robbe Jaime de la Rocha Marie Rooy Fani Koukouli David DiGregorio Uwe Maskos Boris Gutkin Andrey Yu Verisokin Darya V. Verveyko Dmitry E. Postnov Willy Wong Omid Talakoub Robert Chen Milos Popovic Dmitriy Lisitsyn Eric Drebitz Iris Grothe Sunita Mandon Andreas Kreiter Udo Ernst Peter A. Robinson Xuelong Zhao Kevin M. Aquino John D. Griffiths Grishma Mehta-Pandejee Natasha Gabay James MacLaurin Somwrita Sarkar Tim Kunze Jens Haueisen Thomas R. Knösche Subutai Ahmad Yuwei Cui Marcus Lewis Jeff Hawkins Simona Olmi Spase Petkoski Fabrice Bartolomei Maxime Guye Viktor Jirsa Hazem Toutounji Daniel Durstewitz Matteo Cantarelli Adrian Quintana Boris Marin Matt Earnshaw Padraig Gleeson Robert Court Robert McDougal R. Angus Silver Salvador Dura-Bernal Stephen Larson William W. Lytton Giovanni Idili Lorenzo Posani Simona Cocco Karel Ježek Rémi Monasson School of Psychology Faculty of Health & Human Sciences Plymouth University Plymouth Devon PL4 8AA UK Institute of Molecular Biology and Biotechnology (IMBB) Foundation for Research and Technology-Hellas (FORTH) Heraklion Crete Greece Okinawa Institute of Science and Technology Graduate University Okinawa Japan Wellcome Trust Centre for Neuroimaging Institute of Neurology UCL London WC1N 3BG UK School of Engineering and Informatics University of Sussex Brighton BN1 9QJ UK Graduate School Okinawa Institute of Science and Technology Okinawa 904-0495 Japan Computational Neuroscience Unit Okinawa Institute of Science and Technology Okinawa 904-0495 Japan Cognitive Neuroscience Area Scuola Internazionale Superiore di Studi Avanzati Trieste 34136 Italy Kavli Institute for Systems Neuroscience NTNU Trondheim 7030 Norway Institut de la Vision Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Paris 75012 France Department of Engineering University of Cambridge Cambridge Cambridgeshire CB2 1PZ UK Ernst Strüngmann Institute for Neuroscience Max Planck Society Frankfurt Germany Frankfurt Institute for Advanced Studies Frankfurt Germany Neural Systems Analysis Research Center Caesar An Associate of the Max Planck Society Bonn Germany Max Planck Institute for Biological Cybernetics Tübingen Germany Bernstein Center for Computational Neuroscience Tübingen Germany Present Address: Biomedical Engineering Department Georgia Institute of Technology Atlanta GA 30306 USA Department of Neurobiology University of Chicago Chicago IL 60637 USA Department of Organismal Biology and Anatomy University of Chicago Chicago IL 60637 USA Committee on Computational Neuroscience University of Chicago Chicago IL 60637 USA Institut de la Vision Sorbonne Universités INSERM Paris France Laboratoire de Physique Statistique Ecole Normale Supérieure Paris France Institute of Molecular Life Sciences University of Zürich 8057 Zürich Switzerland Institute of Neuroinformatics Univer

来源：评论

学校读者我要写书评

暂无评论

Proceedings from the 9th annual conference on the science of dissemination and implementation: Washington, DC, USA. 14-15 December 2016

引用

Implement Sci 2017年第SUPPL 1期12卷 48-48页

作者： David Chambers Lisa Simpson Gila Neta Ulrica von Thiele Schwarz Antoinette Percy-Laurry Gregory A. Aarons Ross Brownson Amanda Vogel Shannon Wiltsey Stirman Kenneth Sherr Rachel Sturke Wynne E. Norton Allyson Varley Cynthia Vinson Lisa Klesges Suzanne Heurtin-Roberts M. Rashad Massoud Leighann Kimble Arne Beck Claire Neely Jennifer Boggs Carmel Nichols Wen Wan Erin Staab Neda Laiteerapong Nathalie Moise Ravi Shah Susan Essock Margaret Handley Amy Jones Jay Carruthers Karina Davidson Lauren Peccoralo Lloyd Sederer Todd Molfenter Ashley Scudder Sarah Taber-Thomas Kristen Schaffner Amy Herschell Eva Woodward Jeffery Pitcock Mona Ritchie JoAnn Kirchner Julia E. Moore Sobia Khan Shusmita Rashid Jamie Park Melissa Courvoisier Sharon Straus Daniel Blonigen Allison Rodriguez Luisa Manfredi Andrea Nevedal Joel Rosenthal David Smelson Christine Timko Nicole Stadnick Jennifer Regan Miya Barnett Anna Lau Lauren Brookman-Frazee Erick Guerrero Karissa Fenwick Yinfei Kong Gregory Aarons Rebecca Lengnick-Hall Benjamin Henwood Nina Sayer Craig Rosen Robert Orazem Brandy Smith Lindsey Zimmerman David Lounsbury Rachel Kimerling Jodie A. Trafton Steven Lindley Rahul Bhargava Hal Roberts Laura Gibson Gabriel J. Escobar Vincent Liu Benjamin Turk Arona Ragins Patricia Kipnis Ashley Ketterer Gruszkowski Michael W. Kennedy Emily Rentschler Drobek Lior Turgeman Aleksandra Sasha Milicevic Terrence L. Hubert Larissa Myaskovsky Youxu C. Tjader Robert J. Monte Kathryn G. Sapnas Edmond Ramly Diane R Lauver Christie M Bartels Shereef Elnahal Andrea Ippolito Hillary Peabody Carolyn Clancy Randall Cebul Thomas Love Douglas Einstadter Shari Bolen Brook Watts Vera Yakovchenko Angela Park William Lukesh Donald R. Miller David Thornton Mari-Lynn Drainoni Allen L. Gifford Shawna Smith Julia Kyle Mark S Bauer Daniel Eisenberg Celeste Liebrecht Michelle Barbaresso Amy Kilbourne Elyse Park Giselle Perez Jamie Ostroff Sarah Greene Michael Parchman Brian Austin Eric Larson Stefanie Ferreri Chris Shea Megan Smith Kea Turner Jennifer Bacci Kyle Bigham Geoffr Division of Cancer Control and Population Sciences National Cancer Institute Rockville MD 20850 USA AcademyHealth Washington DC 20009 USA Department of Learning Informatics Management and Ethics Karolinska Institutet Stockholm 17177 Sweden Department of Psychiatry University of California San Diego San Diego CA 92093 USA George Warren Brown School of Social Work Washington University in St. Louis St. Louis MO 63130 USA Center for Global Health National Cancer Institute Rockville MD 20850 USA Dissemination and Training Division VA National Center for PTSD Palo Alto CA 94305 USA Department of Global Health University of Washington Seattle WA 98105 USA Center for Global Health Studies Fogarty International Center National Institutes of Health Bethesda MD 20912 USA School of Public Health University of Alabama at Birmingham Birmingham AL 35243 USA School of Public Health University of Memphis Memphis TN 38152 USA USAID Applying Science to Strengthen and Improve Systems (ASSIST) Project Bethesda Maryland 20814 USA Institute for Health Research Kaiser Permanente Denver CO 80231 USA ICSI Institute for Clinical Systems Improvement Bloomington MN 55425 USA Medicine University of Chicago Chicago IL 60637 USA Medicine Columbia University Medical Center New York NY 10032 USA Psychiatry Columbia University New York NY 10032 USA General Internal Medicine Epidemiology and Biostatistics University of California San Francisco San Francisco CA 94110 USA New York State Office of Mental Health New York NY 10001 USA Medicine Icahn School of Medicine at Mount Sinai New York NY 10029 USA Center for Health Enhancement System Studies University of Wisconsin Madison WI 53706 USA Department of Psychiatry University of Pittsburgh Pittsburgh PA 15213 USA Psychology University at Buffalo Buffalo NY 14260 USA Department of Psychology West Virginia University Morgantown WV 26506 USA MIRECC VA North Little Rock AR 72114 USA QUERI for Team-Based Behavioral Health Centr

来源：评论

学校读者我要写书评

暂无评论

New Kinematic Notation and Automatic Generation of Symbolic Dynamics Equations for Space Robots 33

New Kinematic Notation and Automatic Generation of Symbolic ...

引用

第三十三届中国控制会议

作者： ZHANG Hui JIA Yingmin DU Junping ZHANG Jun The Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and TechnologyBeijing University of Posts and Telecommunications School of Electronic and Information Engineering Beihang University (BUAA)

ISBN: (纸本)9781479947249

To verify and evaluate the performance of a space robot controller,kinematics and dynamics of the system have to be formed beforehand for computer *** paper is devoted to develop a new kinematic notation for space robots and to come up with an open source of Matlab subroutines for the propose of obtaining the proper dynamics equations of space robots in symbolic forms *** the new kinematic notation,we will present the general form and two special *** is then demonstrated through an example the advantages such as flexible assignment of frames on space robots,being able to describe multi-DOF joint and achieve a consistent description for multi-arm space *** the second part,we adopt the Lagrangian Formulation for forming the procedures to automatically generate the dynamics equations of space robots in symbolic *** example is then provided to demonstrate the effectiveness of closed-loop simulation adopting the obtained symbolic equations.

关键词： Space Robots,Kinematics,Dynamics,Symbolic Dynamics Equations,Lagrangian

来源：评论

学校读者我要写书评

暂无评论

Distributed Adaptive Two-stage Kalman Filter for Target Tracking in the Presence of Unknown Dynamic Bias 33

Distributed Adaptive Two-stage Kalman Filter for Target Trac...

引用

第三十三届中国控制会议

作者： ZHANG Cui JIA Yingmin DU Junping ZHANG Jun The Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and TechnologyBeijing University of Posts and Telecommunications School of Electronic and Information Engineering Beihang University (BUAA)

ISBN: (纸本)9781479947249

This paper is concerned with the problem of tracking target with multiple sensors in the presence of unknown dynamic bias. A suboptimal adaptive two-stage Kalman filter(ATKF) is designed with two reduce-order filters to estimate the target state and the dynamic bias in parallel when the bias model information is incomplete. Moreover, a distributed adaptive two-stage Kalman filter(DATKF) is developed for multi-sensor system based on the ATKF. The effectiveness of the ATKF and the DATKF are illustrated by the Monte Carlo simulation results.

关键词： Dynamic Bias,Adaptive Two-stage Kalman Filter,Distributed Fusion,Multi-sensor System

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：